## Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |

### From inside the book

Results 1-3 of 86

Page 237

If x is not optimal for the primal

= 0 , x2 = 6 , and yı = 0 , y2 = 2 , yz = 0 , with cx = 30 = yb . This x is feasible for the

...

If x is not optimal for the primal

**problem**, then y is not feasible for the dual**problem**. To illustrate , after one iteration for the Wyndor Glass Co .**problem**, x ,= 0 , x2 = 6 , and yı = 0 , y2 = 2 , yz = 0 , with cx = 30 = yb . This x is feasible for the

...

Page 287

For any linear programming

label each of the following statements as true or false and then justify your

answer . ( a ) The sum of the number of functional constraints and the number of ...

For any linear programming

**problem**in our standard form and its dual**problem**,label each of the following statements as true or false and then justify your

answer . ( a ) The sum of the number of functional constraints and the number of ...

Page 288

sic solution for the dual

draw your conclusions about whether these two basic solutions are optimal for

their respective

sic solution for the dual

**problem**by using Eq . ( 0 ) for the pri - mal**problem**. Thendraw your conclusions about whether these two basic solutions are optimal for

their respective

**problems**. 1 ( d ) Solve the dual**problem**graphically . Use this ...### What people are saying - Write a review

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### Contents

SUPPLEMENT TO APPENDIX 3 | 3 |

Problems | 6 |

An Algorithm for the Assignment Problem | 18 |

Copyright | |

59 other sections not shown

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### Common terms and phrases

activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming Maximize million Minimize month needed node nonbasic variables nonnegative objective function obtained operations optimal optimal solution original parameters path plant possible presented primal problem Prob procedure profit programming problem provides range remaining resource respective resulting revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion transportation unit values weeks Wyndor Glass zero